{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: jieba in c:\\programdata\\anaconda3\\lib\\site-packages (0.42.1)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEPRECATION: pandas 0.23.4 has a non-standard dependency specifier pytz>=2011k. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pandas or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\n"
     ]
    }
   ],
   "source": [
    "!pip install jieba"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: wordcloud in c:\\programdata\\anaconda3\\lib\\site-packages (1.9.4)\n",
      "Requirement already satisfied: numpy>=1.6.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from wordcloud) (1.15.1)\n",
      "Requirement already satisfied: pillow in c:\\programdata\\anaconda3\\lib\\site-packages (from wordcloud) (9.5.0)\n",
      "Requirement already satisfied: matplotlib in c:\\programdata\\anaconda3\\lib\\site-packages (from wordcloud) (2.2.3)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\programdata\\anaconda3\\lib\\site-packages (from matplotlib->wordcloud) (0.10.0)\n",
      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from matplotlib->wordcloud) (2.2.0)\n",
      "Requirement already satisfied: python-dateutil>=2.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from matplotlib->wordcloud) (2.7.3)\n",
      "Requirement already satisfied: pytz in c:\\programdata\\anaconda3\\lib\\site-packages (from matplotlib->wordcloud) (2018.5)\n",
      "Requirement already satisfied: six>=1.10 in c:\\programdata\\anaconda3\\lib\\site-packages (from matplotlib->wordcloud) (1.11.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from matplotlib->wordcloud) (1.0.1)\n",
      "Requirement already satisfied: setuptools in c:\\programdata\\anaconda3\\lib\\site-packages (from kiwisolver>=1.0.1->matplotlib->wordcloud) (40.2.0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEPRECATION: pandas 0.23.4 has a non-standard dependency specifier pytz>=2011k. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pandas or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\n"
     ]
    }
   ],
   "source": [
    "!pip install wordcloud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import jieba\n",
    "from wordcloud import WordCloud\n",
    "import matplotlib.pyplot as plt\n",
    "import imageio\n",
    "%matplotlib inline\n",
    "f=open('mess.txt',encoding ='utf-8')\n",
    "t=f.read() \n",
    "f.close()\n",
    "words = jieba.lcut(t)\n",
    "txt =' '.join(words)\n",
    "image = imageio.imread(r'horse.png')\n",
    "w = WordCloud(font_path = 'FZFSJW.TTF',background_color='white', mask = image)\n",
    "w.generate(txt)\n",
    "w.to_file('test.png')\n",
    "plt.imshow(w, interpolation = 'bilinear')\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "import jieba.analyse\n",
    "import jieba.posseg\n",
    "\n",
    "def get_sentence(text):\n",
    "    split_num=0\n",
    "    sentences=[]\n",
    "    for paragraph in text.split(\"\\n\"):\n",
    "        if paragraph:\n",
    "            sentence_num=0\n",
    "            for paragraph in re.split(\"!|。|？\",paragraph):\n",
    "                if paragraph:\n",
    "                    mark=[]\n",
    "                    if split_num==0:\n",
    "                        mark.append(\"FIRSTSECTION\")\n",
    "                    if sentence_num==0:\n",
    "                        mark.append(\"FIRSTSENTENCE\")\n",
    "                    sentences.append({\"text\":paragraph,\"pos\":{\"x\":split_num,\"y\":sentence_num,\"mark\":mark}})\n",
    "                    sentence_num=sentence_num+1\n",
    "            split_num=split_num+1\n",
    "            sentences[-1][\"pos\"][\"mark\"].append(\"LASTSENTENCE\")\n",
    "    for i in range(0,len(sentences)):\n",
    "        if sentences[i][\"pos\"][\"x\"]==sentences[-1][\"pos\"][\"x\"]:\n",
    "            sentences[1][\"pos\"][\"mark\"].append(\"LASTSECTION\")\n",
    "    return sentences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "对文本进行分句:\n",
      " [{'text': '2015年7月31日，北京获得2022年第24届冬奥会的举办权', 'pos': {'x': 0, 'y': 0, 'mark': ['FIRSTSECTION', 'FIRSTSENTENCE']}}, {'text': '第24届冬奥会将于2022年2月4日至2月20日在中国北京举行，北京也将成为历史上第一座既举办过夏奥会又举办过冬奥会的城市', 'pos': {'x': 0, 'y': 1, 'mark': ['FIRSTSECTION', 'LASTSENTENCE', 'LASTSECTION']}}, {'text': '2022年北京冬奥会计划使用25个场馆，场馆分布在3个赛区，分别是北京赛区、延庆赛区和张家口赛区', 'pos': {'x': 1, 'y': 0, 'mark': ['FIRSTSENTENCE', 'LASTSENTENCE']}}, {'text': '北京是中华人民共和国的首都，是全国政治中心、文化中心、国际交往中心、科技创新中心', 'pos': {'x': 2, 'y': 0, 'mark': ['FIRSTSENTENCE']}}, {'text': '2008年，北京成功举办了第29届夏季奥林匹克运动会', 'pos': {'x': 2, 'y': 1, 'mark': ['LASTSENTENCE']}}]\n"
     ]
    }
   ],
   "source": [
    "sample=open('mess.txt',encoding='utf-8').read()\n",
    "sentences=get_sentence(sample)\n",
    "print(\"对文本进行分句:\\n\",sentences[:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_keywords(text):\n",
    "    keywords=jieba.analyse.extract_tags(text,topK=100,withWeight=False,allowPOS=('n','vn','v'))\n",
    "    return keywords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "对文本进行关键词提取：\n",
      " ['运动员', '冰雪', '赛区', '展现', '赛场', '举办', '飞跃', '举办地', '获得', '中心']\n"
     ]
    }
   ],
   "source": [
    "keywords=get_keywords(sample)\n",
    "print('对文本进行关键词提取：\\n',keywords[:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_weight(sentences,keywords):\n",
    "    for sentence in sentences:\n",
    "        mark=sentence[\"pos\"][\"mark\"]\n",
    "        weightPos=0\n",
    "        if\"FIRSTSECTTON\"in mark:\n",
    "            weightPos=weightPos+2\n",
    "        if\"FIRSTSENTENCE\"in mark:\n",
    "            weightPos=weightPos+2\n",
    "        if\"LASTSENTENCE\"in mark:\n",
    "            weightPos=weightPos+1\n",
    "        if \"LASTSECTION\"in mark:\n",
    "            weightPos=weightPos+1\n",
    "        sentence[\"weightPos\"]=weightPos\n",
    "    index=[\"冬梦\",\"飞跃\"]\n",
    "    for sentence in sentences:\n",
    "        sentence[\"weightCueWords\"]=0\n",
    "        sentence[\"weightKeywords\"]=0\n",
    "    for i in index:\n",
    "        for sentence in sentences:\n",
    "            if sentence[\"text\"].find(i)>=0:\n",
    "                sentence[\"weightCueWords\"]=1\n",
    "    for keyword in keywords:\n",
    "        for sentence in sentences:\n",
    "            if sentence[\"text\"].find(keyword)>=0:\n",
    "                sentence[\"weightKeywords\"]=sentence[\"weightKeywords\"]+1\n",
    "    weight=[]\n",
    "    for sentence in sentences:\n",
    "        sentence[\"weight\"]=sentence[\"weightPos\"] +2 *sentence[\"weightCueWords\"]+sentence[\"weightKeywords\"]\n",
    "        weight.append(sentence[\"weight\"])\n",
    "    return weight"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "文本中每个句子的权重为:\n",
      " [5, 6, 5, 5, 3, 10, 4, 4, 5, 4, 16, 7, 17, 7, 8, 14, 6, 16, 11, 8, 10, 22, 5, 9, 3, 4, 10]\n"
     ]
    }
   ],
   "source": [
    "weight=get_weight(sentences,keywords)\n",
    "print(\"文本中每个句子的权重为:\\n\",weight)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_sum(sentences,keywords,ratio=0.1):\n",
    "    summary=list()\n",
    "    sentences=sorted(sentences,key=lambda k:k['weight'],reverse=True)\n",
    "    length=0\n",
    "    for i in range(len(sentences)):\n",
    "        if length<3:\n",
    "            if i <ratio*len(sentences):\n",
    "                sentence=sentences[i]\n",
    "                summary.append(sentence['text'])\n",
    "                length+=1\n",
    "    return summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "生成自动文摘:\n",
      " 会徽图形整体充满了昂扬向上之激情，奋进飞跃之动感，色彩丰富，构图完美，象征并激发运动员以坚强的意志作为精神的翅膀，在冬残奥赛场上放飞青春梦想！\n",
      "中间舞动的线条流畅且充满韵律，代表举办地起伏的山峦、赛场、冰雪滑道和节日飘舞的丝带，为会徽增添了节日喜庆的视觉感受，也象征着北京冬奥会将在中国春节期间举行\n",
      "冬奥会会徽以汉字“冬”为灵感来源，运用中国书法的艺术形态， 将厚重的东方文化底蕴与国际化的现代 风格融为一体，呈现出新时代的中国新形象、新梦想，传递出新时代中国为办好北京冬奥会，圆冬奥之梦，实现“三亿人参与冰雪运动”目标，圆体育强国之梦，推动世界冰雪运动发展，为国际奥林匹克运动做出新贡献的不懈努力和美好追求\n"
     ]
    }
   ],
   "source": [
    "abstract_content='\\n'.join(get_sum(sentences,keywords))\n",
    "print('生成自动文摘:\\n',abstract_content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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